Knowledge is the foundation of the new economy. Continuously expanding knowledge makes continuous learning, training, education, and consulting more important now than ever before. In the United States, an extraordinary amount of money is being spent in the area of education, and the corporate electronic learning (or e-Learning) market is expected to increase continually over the coming years.
In recent years, the concept of business war-gaming has emerged as a new source of e-Learning. Business war-gaming is the management counterpart of combat simulation, where battles are fought in marketplaces rather than battlefields, and where the main players are people and programs (manufacturers, distributors, resellers, and business customers), and jobs or organizations. Business war-gaming provides a forum for e-Learning by allowing experimentation of alternative management decision-making policies under pre-specified scenarios.
A major difference between business war-gaming and combat simulation is the technology used to build each. As opposed to the top-down, discrete event approach favored by combat simulations, business war-gaming uses bottom-up, agent-based simulation wherein software agents programmed with rules of engagement represent individuals or organizations. In this world, human players represent organizations, and the collective behavior of the individual software agents model markets and market forces.
Business war-gaming starts out today and plays into the future. It considers “what if” scenarios impacted simultaneously by technological innovations, political and regulatory changes, business and economic decisions, and the evolution of consumer preferences due to social and competitive forces. By playing through those possible alternative scenarios, participants “experience the future” of both—the strategies as well as the results. By interacting amongst themselves in these different scenarios, the participants are able to construct accurate and robust strategies.
Recent models of business war-gaming simulations have attempted to model a global economic environment. These simulations, however, do not have a fully interlinked infrastructure that can be dynamically configured.
For the reasons stated above, and for other reasons stated below which will become apparent to those skilled in the art upon reading and understanding the present specification, there is a need for a global industrial simulation environment that can model interlinked economies, interlinked management functionalities, and interlinked agents that interact in the environment. There is also a need for operational data that can be easily customized in the simulation environment, so that rules of engagement can be dynamically configured.